Zobrazeno 1 - 10
of 27 521
pro vyhledávání: '"Chhabra A"'
Autor:
Hunter CW, Deer TR, Jones MR, Chang Chien GC, D'Souza RS, Davis T, Eldon ER, Esposito MF, Goree JH, Hewan-Lowe L, Maloney JA, Mazzola AJ, Michels JS, Layno-Moses A, Patel S, Tari J, Weisbein JS, Goulding KA, Chhabra A, Hassebrock J, Wie C, Beall D, Sayed D, Strand N
Publikováno v:
Journal of Pain Research, Vol Volume 15, Pp 2683-2745 (2022)
Corey W Hunter,1,2 Timothy R Deer,3 Mark R Jones,4 George Chiang Chien,5 Ryan S D’Souza,6 Timothy Davis,7 Erica R Eldon,2 Michael F Esposito,8 Johnathan H Goree,9 Lissa Hewan-Lowe,2 Jillian A Maloney,10 Anthony J Mazzola,2 John S Michels,4 Annie La
Externí odkaz:
https://doaj.org/article/ea8134a5757348c0a2cd192bdc9c8984
Autor:
Yadav Kanchan, Das Megha, Mishra Nitesh Kumar, Chhabra Anuj, Mishra Archana, Srivastava Sunita, Sharma Poonam, Yadav Sanjeev Kumar, Parmar Avanish Singh
Publikováno v:
Nanotechnology Reviews, Vol 11, Iss 1, Pp 1643-1657 (2022)
Externí odkaz:
https://doaj.org/article/e71181c00add4eda824548da4d45e7ed
Autor:
Roychowdhury, Sujoy, Soman, Sumit, Ranjani, H. G., Chhabra, Vansh, Gunda, Neeraj, Bandyopadhyay, Subhadip, Bala, Sai Krishna
A plethora of sentence embedding models makes it challenging to choose one, especially for domains such as telecom, rich with specialized vocabulary. We evaluate multiple embeddings obtained from publicly available models and their domain-adapted var
Externí odkaz:
http://arxiv.org/abs/2406.12336
Numerous recent X-ray observations of coronal loops in both active regions (ARs) and solar flares have shown clearly that elemental abundances vary with time. Over the course of a flare, they have been found to move from coronal values towards photos
Externí odkaz:
http://arxiv.org/abs/2406.04473
Large Language Models (LLMs) have achieved state-of-the-art performance at zero-shot generation of abstractive summaries for given articles. However, little is known about the robustness of such a process of zero-shot summarization. To bridge this ga
Externí odkaz:
http://arxiv.org/abs/2406.03993
Influence functions offer a robust framework for assessing the impact of each training data sample on model predictions, serving as a prominent tool in data-centric learning. Despite their widespread use in various tasks, the strong convexity assumpt
Externí odkaz:
http://arxiv.org/abs/2405.03869
Autor:
Echeverri, Daniel, Xuan, Jerry W., Monnier, John D., Delorme, Jacques-Robert, Wang, Jason J., Jovanovic, Nemanja, Horstman, Katelyn, Ruane, Garreth, Mennesson, Bertrand, Serabyn, Eugene, Mawet, Dimitri, Wallace, J. Kent, Hillman, Sofia, Baker, Ashley, Bartos, Randall, Calvin, Benjamin, Cetre, Sylvain, Doppmann, Greg, Finnerty, Luke, Fitzgerald, Michael P., Hsu, Chih-Chun, Liberman, Joshua, Lopez, Ronald, Millar-Blanchaer, Maxwell, Morris, Evan, Pezzato, Jacklyn, Ruffio, Jean-Baptiste, Sappey, Ben, Schofield, Tobias, Skemer, Andrew J., Wang, Ji, Xin, Yinzi, Anugu, Narsireddy, Chhabra, Sorabh, Ibrahim, Noura, Kraus, Stefan, Schaefer, Gail H., Lanthermann, Cyprien
Vortex fiber nulling (VFN) is a technique for detecting and characterizing faint companions at small separations from their host star. A near-infrared ($\sim2.3 \mu$m) VFN demonstrator mode was deployed on the Keck Planet Imager and Characterizer (KP
Externí odkaz:
http://arxiv.org/abs/2403.17295
Autor:
Askari, Hadi, Chhabra, Anshuman, von Hohenberg, Bernhard Clemm, Heseltine, Michael, Wojcieszak, Magdalena
Polarization, declining trust, and wavering support for democratic norms are pressing threats to U.S. democracy. Exposure to verified and quality news may lower individual susceptibility to these threats and make citizens more resilient to misinforma
Externí odkaz:
http://arxiv.org/abs/2403.13362
An expansion of cross-sectional area directly impacts the mass flow along a coronal loop, and significantly alters the radiative and hydrodynamic evolution of that loop as a result. Previous studies have found that an area expansion from chromosphere
Externí odkaz:
http://arxiv.org/abs/2403.12358
Autor:
Khurma, Ruba Abu, Alhenawi, Esraa, Braik, Malik, Hashim, Fatma A., Chhabra, Amit, Castillo, Pedro A.
It is of paramount importance to enhance medical practices, given how important it is to protect human life. Medical therapy can be accelerated by automating patient prediction using machine learning techniques. To double the efficiency of classifier
Externí odkaz:
http://arxiv.org/abs/2404.07216